3D CAD model retrieval with perturbed Laplacian spectra

This paper presents a novel approach to the 3D CAD model retrieval, whereby the 3D models are treated and matched as undirected graphs. While there is much success made in the matching of graphs based on their spectral decomposition, most of these approaches consider smooth surfaces and are not suitable for CAD models because of their complex topology and singular structure. In the proposed approach, the models are simplified based on the piecewise flat properties of the surfaces first, and a perturbed Laplacian spectrum approach is then applied to characterize the shape. These spectral values are used as samples for spectral distribution estimation. The perturbed spectral distributions of different models are then compared by their KL-divergence for model retrieval. The proposed approach is tested with models from known 3D CAD database for verification.

► Develop a 3D CAD model retrieval approach with undirected graphical models. ► A perturbed Laplacian spectrum approach is developed to characterize the complex topology and singular structure of 3D CAD models. ► The perturbed spectral distributions are compared by their KL-divergence for model retrieval. ► The approach is robust and stable.